The Effects of Naturally Produced Dust Particles on Radiative Transfer

  • C. Spyrou
  • G. Kallos
  • C. Mitsakou
  • P. Athanasiadis
  • C. Kalogeri
Conference paper
Part of the Springer Atmospheric Sciences book series (SPRINGERATMO)

Abstract

Mineral dust has a profound effect on the radiative budget and energy distribution of the atmosphere. By absorbing and scattering the solar radiation aerosols reduce the amount of energy reaching the surface. In addition aerosols enhance the greenhouse effect by absorbing and emitting longwave radiation. Desert dust forcing exhibits large regional and temporal variability due to its short lifetime and diverse optical properties further complicate the quantification of the Direct Radiative Effect (DRE). The complexity of the above processes, indicate the need of an integrated approach in order to examine these impacts. To this end the radiative transfer module RRTMG has been incorporated into the framework of the SKIRON model. The updated system was used to perform a 6-year long simulation over the Mediterranean region. As it was found, the most profound effect dust clouds have in areas away from the sources is the surface cooling through the “shading” effect. The long wave radiation forcing below and above the dust cloud is considerable and drives changes in the tropospheric temperature. In general dust particles cause warming near the ground and at mid-tropospheric layers and at the same time cooling of the lower troposphere.

Keywords

Dust Particle Outgoing Longwave Radiation Longwave Radiation Dust Cloud Incoming Solar Radiation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Astitha M, Kallos G, Spyrou C, O’Hirok W, Lelieveld J, Denier van der Gon HAC (2010) Modelling the chemically aged and mixed aerosols over the eastern central Atlantic Ocean – potential impacts. Atmos Chem Phys 10:5797–5822. doi: 10.5194/acp-10-5797-2010 CrossRefGoogle Scholar
  2. Barker HW, Pincus R, Morcrette JJ, The Monte-Carlo Independent Column Approximation (2003) Application within large-scale models. In: Proceedings of the GCSS/ARM workshop on the representation of cloud systems in large-scale models, Kananaskis, Alberta, Canada, 10ppGoogle Scholar
  3. Clough SA, Shephard MW, Mlawer EJ, Delamere JS, Iacono MJ, Cady-Pereira K, Boukabara S, Brown PD (2005) Atmospheric radiative transfer modeling: a summary of the AER codes. J Quant Spectrosc Radiat Transf 91:233–244CrossRefGoogle Scholar
  4. Dufrense JL, Gautier C, Ricchiazzi P (2001) Longwave scattering of mineral aerosols. J Atmos Sci 59:959–1966Google Scholar
  5. Haywood JM et al (2003) Radiative properties and direct Radiative effect of Saharan dust measured by the C-130 aircraft during SHADE: 1. Solar spectrum. J Geophys Res 108(D18):8577. doi: 10.1029/2002JD002687 CrossRefGoogle Scholar
  6. Helmert J, Heinold B, Tegen I, Hellmuth O, Wendisch M (2007) On the direct and semidirect effects of Saharan dust over Europe: a modelling study. J Geophys Res 112. doi: 10.1029/2006JD007444
  7. Iacono MJ, Delamere JS, Mlawer EJ, Clough SA (2003) Evaluation of upper tropospheric water vapor in the NCAR community climate model (CCM3) using modeled and observed HIRS radiances. J Geophys Res 108(D2):4037. doi: 10.1029/2002JD002539 CrossRefGoogle Scholar
  8. Iacono MJ, Delamere JS, Mlawer EJ, Shephard MW, Clough SA, Collins WD (2008) Radiative forcing by long-lived greenhouse gases: calculations with the AER radiative transfer models. J Geophys Res 113:D13103. doi: 10.1029/2008JD009944 CrossRefGoogle Scholar
  9. Intergovernmental Panel on Climate Change (IPCC) (2007), Climate change 2007: the physical science basis, Cambridge University Press, UKGoogle Scholar
  10. Kallos G, Spyrou C, Astitha M, Mitsakou C, Solomos S, Kushta J, Pytharoulis I, Katsafados P, Mavromatidis E, Papantoniou N, Vlastou G (2009) Ten-year operational dust forecasting – recent model development and future plans. IOP Conf Ser Earth Environ Sci 7(2009). doi: 10.1088/1755-1307/7/1/012012
  11. Kaufman YJ, Koren I, Remer LA, Rosenfeld D, Rudich Y (2005) The effect of smoke, dust and pollution aerosol on shallow cloud development over the Atlantic 160 Ocean. Proc Natl Acad Sci USA 102:11207–11212CrossRefGoogle Scholar
  12. Levin Z, Teller A, Ganor E, Yin Y (2005) On the interactions of mineral dust, sea-salt particles and clouds: a measurement and modelling study from the Mediterranean Israeli Dust Experiment campaign. J Geophys Res 110:D20202. doi: 10.1029/2005JD005810 CrossRefGoogle Scholar
  13. Liao H, Seinfeld JH (1998) Radiative forcing by mineral dust aerosols: sensitivity to key variables. J Geophys Res 103(D):31637–31645CrossRefGoogle Scholar
  14. Mlawer EJ, Taubman SJ, Brown PD, Iacono MJ, Clough SA (1997) RRTM, a validated correlated-k model for the longwave. J Geophys Res 102:16,663–16,682CrossRefGoogle Scholar
  15. Morcrette JJ, Barker HW, Cole JNS, Iacono MJ, Pincus R (2008) Impact of a new radiation package, McRad, in the ECMWF integrated forecast system. Mon Weather Rev 136(12):4773–4798, doi:  10.1175/2008MWR2363.1 Google Scholar
  16. Oreopoulos L, Barker HW (1999) Accounting for subgrid-scale cloud variability in a multi-layer 1-D solar radiative transfer algorithm. Q J R Meteor Soc 125:301–330Google Scholar
  17. Pincus R, Barker HW, Morcrette JJ (2003) A fast, flexible, approximate technique for computing radiative transfer in inhomogeneous clouds. J Geophys Res 108(D13):4376. doi: 10.1029/2002JD003322 CrossRefGoogle Scholar
  18. Sokolik IN, Toon OB (1996) Direct radiative forcing by anthropogenic airborne mineral aerosols. Nature 381:681–683CrossRefGoogle Scholar
  19. Solomos S, Kallos G, Kushta J, Astitha M, Tremback C, Nenes A, Levin Z (2011) An integrated modeling study on the effects of mineral dust and sea salt particles on clouds and precipitation. Atmos Chem Phys 11:873–892. doi: 10.5194/acp-11-873-2011 CrossRefGoogle Scholar
  20. Spyrou C, Mitsakou C, Kallos G, Louka P, Vlastou G (2010) An improved limited area model for describing the dust cycle in the atmosphere. J Geophys Res 115:D17211. doi: 10.1029/2009JD013682 CrossRefGoogle Scholar
  21. Tegen I (2003) Modeling the mineral dust aerosol cycle in the climate system. Q Sci Rev 22:1821–1834CrossRefGoogle Scholar
  22. Tegen I, Lacis AA (1996) Modeling of particle size distribution and its influence on the radiative properties of mineral dust aerosol. J Geophys Res 101:19,237–19,244CrossRefGoogle Scholar
  23. Wilks DS (1995) Statistical methods in the atmospheric sciences, Academic Press NY, pp 233–277Google Scholar
  24. Yoshioka M, Mahowald N, Dufresne JL, Luo C (2005) Simulation of absorbing aerosol indices for African dust. J Geophys Res 110:D18S17. doi: 10.1029/2004JD005276 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • C. Spyrou
    • 1
  • G. Kallos
    • 1
  • C. Mitsakou
    • 1
  • P. Athanasiadis
    • 1
  • C. Kalogeri
    • 1
  1. 1.Atmospheric Modeling and Weather Forecasting Group, Department of PhysicsUniversity of AthensAthensGreece

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